Protein evolution speed depends on its stability and abundance and on chaperone concentrations

Agozzino, Luca; Dill, Ken A.

doi:10.1073/pnas.1810194115

Cited by 69 publications

(73 citation statements)

References 44 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Such an observation is fairly intuitive, as mutations which 273 alter binding strength correctly or incorrectly are more strongly selected or purified 274 respectively in the nondeterministic assemblies. This is in good agreement with the 275 observation that unstable proteins adapt more quickly [18].…”

supporting

confidence: 84%

Evolution of interface binding strengths in simplified model of protein quaternary structure

Leonard

Ahnert

2019

Preprint

View full text Add to dashboard Cite

The self-assembly of proteins into protein quaternary structures is of fundamental importance to many biological processes, and protein misassembly is responsible for a wide range of proteopathic diseases. In recent years, abstract lattice models of protein self-assembly have been used to simulate the evolution and assembly of protein quaternary structure, and to provide a tractable way to study the genotype-phenotype map of such systems. Here we generalize these models by representing the interfaces as mutable binary strings. This simple change enables us to model the evolution of interface strengths, interface symmetry, and deterministic assembly pathways. Using the generalized model we are able to reproduce two important results established for real protein complexes: The first is that protein assembly pathways are under evolutionary selection to minimize misassembly. The second is that the assembly pathway of a complex mirrors its evolutionary history, and that both can be derived from the relative strengths of interfaces. These results demonstrate that the generalized lattice model offers a powerful new framework for the study of protein self-assembly processes and their evolution.Protein complexes assemble by joining individual proteins together through interacting binding sites. Because of the long time scales of biological evolution, it can be difficult to reconstruct how these interactions change over time. We use simplified representations of proteins to simulate the evolution of these complexes on a computer. In some cases the order in which the complex assembles is crucial. We show that biological evolution increases the strength of interactions that must occur earlier, and decreases the strength of later interactions. Similar knowledge of interactions being preferred to be stronger or weaker can also help to predict the evolutionary ancestry of a complex. While these simulations are not realistic enough to make exact predictions, this general link between ordered pathways in assembly and evolution matches well-established observations that have been made in real protein complexes. This means that our model provides a powerful framework for the study of protein complex assembly and evolution. Introduction 1 Many proteins self-assemble into protein quaternary structures, which fulfill a multitude 2 of functions across a wide range of biological processes [1]. Abstract models trade off 3 the complexity arising from conformations, buried surfaces, cooperative binding, etc., 4 but still retain qualitative realism. A general class of polyomino tile self-assembly 5 models have strong analytic potential while maintaining semblance to protein quatenary 6 structure. 7 The polyomino self-assembly model [2] combines lattice tile self-assembly with a 8 quantification of biological complexity, examining the relationship between genetic 9 description length and phenotypic complexity. The same model was developed and 10 expanded with evolutionary dynamics by Johnston et al. [3], and used to probe general 11 properti...

show abstract

supporting

confidence: 84%

Evolution of interface binding strengths in simplified model of protein quaternary structure

Leonard

Ahnert

2019

Preprint

View full text Add to dashboard Cite

show abstract

“…If that mutation causes misfolding or reduces folding stability, the cell's fitness V is reduced by the protein's abundance A (Equation 14). Or, if that mutation causes protein aggregation (79), then the effect on cell fitness is proportional to A 2 (63). Such protein folding contributions to fitness and evolution rates successfully predict the mutational fitness effects in viruses and simple cells (63, 81).…”

Section: Proteins That Are Least Abundant In a Cell Are Fastest To Evmentioning

confidence: 99%

“…Other factors affecting the speed are the rate of mutations and the effective population size (64,65). To study the principle of how evolution speed depends on landscape shape, Equation 12 is combined with the simplest nonflat landscape, which has a slope that is linear in the number m of mutations; V (m) = constant × m away from the optimal sequence (63).…”

Section: Evolution Speeds Range From Days To Millions Of Yearsmentioning

confidence: 99%

“…In contrast, cooling does not destabilize folded proteins, so cells are slower to adapt to cooling (path ➍). In summary, cells should adapt to warm climates faster than to colder ones (63). This prediction has not been tested, as far as we know, but experiments show that a mesophile can successfully adapt to a warmer environment (71).…”

Section: Cells Acclimate Faster To Hotter Than Colder Environmentsmentioning

confidence: 99%

“…Through a cell's evolution, the expression level of a gene (and thus the abundance level of its protein) can change (Figure 7). Proteins that are abundant tend to evolve slowly (63,(72)(73)(74)(75)(76)(77)(78)(79)(80). This is called the expression level-substitution rate anticorrelation.…”

Section: Proteins That Are Least Abundant In a Cell Are Fastest To Evmentioning

confidence: 99%

See 2 more Smart Citations

How Do Cells Adapt? Stories Told in Landscapes

Agozzino

Balázsi

Wang

et al. 2020

Annu. Rev. Chem. Biomol. Eng.

Self Cite

View full text Add to dashboard Cite

Cells adapt to changing environments. Perturb a cell and it returns to a point of homeostasis. Perturb a population and it evolves toward a fitness peak. We review quantitative models of the forces of adaptation and their visualizations on landscapes. While some adaptations result from single mutations or few-gene effects, others are more cooperative, more delocalized in the genome, and more universal and physical. For example, homeostasis and evolution depend on protein folding and aggregation, energy and protein production, protein diffusion, molecular motor speeds and efficiencies, and protein expression levels. Models provide a way to learn about the fitness of cells and cell populations by making and testing hypotheses.

show abstract

An experimental test of temperature‐dependent selection on mitochondrial haplotypes in Callosobruchus maculatus seed beetles

Immonen

Berger

Sayadi

et al. 2020

Ecology and Evolution

View full text Add to dashboard Cite

Mitochondrial DNA (mtDNA) consists of few but vital maternally inherited genes that interact closely with nuclear genes to produce cellular energy. How important mtDNA polymorphism is for adaptation is still unclear. The assumption in population genetic studies is often that segregating mtDNA variation is selectively neutral. This contrasts with empirical observations of mtDNA haplotypes affecting fitness‐related traits and thermal sensitivity, and latitudinal clines in mtDNA haplotype frequencies. Here, we experimentally test whether ambient temperature affects selection on mtDNA variation, and whether such thermal effects are influenced by intergenomic epistasis due to interactions between mitochondrial and nuclear genes, using replicated experimental evolution in Callosobruchus maculatus seed beetle populations seeded with a mixture of different mtDNA haplotypes. We also test for sex‐specific consequences of mtDNA evolution on reproductive success, given that mtDNA mutations can have sexually antagonistic fitness effects. Our results demonstrate natural selection on mtDNA haplotypes, with some support for thermal environment influencing mtDNA evolution through mitonuclear epistasis. The changes in male and female reproductive fitness were both aligned with changes in mtDNA haplotype frequencies, suggesting that natural selection on mtDNA is sexually concordant in stressful thermal environments. We discuss the implications of our findings for the evolution of mtDNA.

show abstract

Protein evolution speed depends on its stability and abundance and on chaperone concentrations

Cited by 69 publications

References 44 publications

Evolution of interface binding strengths in simplified model of protein quaternary structure

Evolution of interface binding strengths in simplified model of protein quaternary structure

How Do Cells Adapt? Stories Told in Landscapes

An experimental test of temperature‐dependent selection on mitochondrial haplotypes in Callosobruchus maculatus seed beetles

Contact Info

Product

Resources

About